IBM and European Union partners create a better way to fight AIDS virus

Washington 02 June 2009IBM was selected for its contributions to the EuResist research project for AIDS treatment as a Computerworld Honors Programme Laureate for 2009. Developed by IBM researchers in Haifa, Israel, the project's new technologies and mathematical models are providing a smarter and more efficient way to choose the best drugs combinations for any given HIV genetic variant. EuResist is a powerful on-line system that helps doctors choose the treatment with the highest probability of halting virus replication and impairing evolution of drug resistance.

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Although there have been tremendous leaps and bounds in the management of the virus that causes AIDS, HIV has the ability to develop resistance to any anti-retroviral compound. This means that doctors need to continuously monitor and prescribe new therapies for the treatment to remain effective. Keeping HIV under control is dependent on choosing the right combination of drugs that work for the longest period of time.

EuResist is the first and only freely available data-driven computational method that predicts the success of a treatment regimen against any given HIV genotype, based not only on viral genotype information, but using analytic technologies to take into account treatment response information from clinical practice. It is also the only system providing the global medical community with an estimate of activity for combination therapy, rather than for individual drugs.

Researchers behind the European Union-funded EuResist project have developed new mathematical prediction models that not only take into account the patient's own history, but tap into the wealth of information that EuResist researchers have amassed. The recent expansion of the EuResist database to include information from more than 33.000 patients and 98.000 therapies, and 370.000 viral load measurements, makes it the world's biggest database centred on HIV resistance and clinical response information.

"EuResist has managed to create the largest clinically oriented anti-retroviral drug resistance database in the world", explained Professor Maurizio Zazzi, EuResist Scientific Co-ordinator and Professor of Microbiology at the University of Siena School of Medicine. "The ability to analyse clinical, laboratory and demographic data accumulated over the years significantly improves prediction of the right combination of drugs that works for the maximum amount of time." These innovations are being provided as a free tool that can help extend the lives of millions of people who are the victims of this disease.

The system's predictions are near 76 percent accurate, outperforming other commonly used HIV resistance prediction tools and also outperformed human experts in the field. To simulate real practice in HIV specialized care, the Engine versus Experts (EVE) study compared EuResist with 10 international experts confronted with 25 case histories, where all the clinical and virological information was available, EuResist's predictions outperformed nine out of ten human experts.

"The EuResist team feels both humbled and privileged by the opportunity to put good science and state-of-the-art technologies at the service of such an important and meaningful cause", noted Yardena Peres, researcher at the IBM Research Lab in Haifa and one of the leaders for the IBM contribution for the EuResist project.

Along with talent from the IBM Research Lab in Haifa, the brains behind the EuResist project come from the EuResist Network, a non-profit partnership of pharmaceutical companies, governmental institutions, and private companies, and its GEIE partners including a European Economic Interest Grouping composed of Karolinska Institute, Max Planck Institute, University of Siena, Informa s.r.l., University of Cologne.

More IBM news is available in the VMW June 2009 article IBM establishes Global Healthcare Centre of Excellence in La Gaude, France and helps Government of Slovenia to build smart health insurance system.


Source: IBM

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